The goal of this research is to study high-resolution image analysis of cervical cells for diagnostic assessment of patients. The discovery of the marker features for the presence of dysplasia or malignant disease expressed in "normal appearing" intermediate cells from the ectocervix has affected the very strategy of prescreening for cervical cancer. If confirmed on a large database of patients, the finding of frank tumor cells could be replaced by the statistical assessment of a limited sample of a patient's intermediate cells to ascertain whether visual review of the patient's sample is required. Complementing the analysis of marker features in cells coming from normal patients, patients with dysplasia, with carcinoma in situ, and with invasive cancer, a new technique has been developed to measure the ploidy of cells appearing in Papanicolaou smears and histological sections. It appears that the rapid availability of this new kind of information may add significant, new prognostic dimensions to the diagnostic techniques being developed. The statistical distribution of the DNA content in individual nuclei has been shown to be significantly correlated with the malignancy of tumors and the patient prognosis. The high-resolution technique for ploidy measurement is proven to be precise, accurate, and fast. We have now completed the measurement of 50 cases designated as either dysplastic or having carcinoma in situ. For each case, this involves the collection of: (1)\intermediate blue cell images from vaginal, cervical, and endocervical smear preparations; (2)\dysplastic cell images from dysplasia cases; (3)\carcinoma in situ cell images from carcinoma in situ cases; (4)\DNA-ploidy patterns of both normal and abnormal cells from the cytology preparations; and (5)\DNA-ploidy patterns of both normal and abnormal cells from histological specimens obtained by biopsy. DNA results are now routinely produced with a variety of parameters that are being correlated with the results of discriminant analysis on the intermediate blue cell populations. (3)